Monday, March 5, 2012

Crowd-data can find drug and vaccine side effects

The social crowd has proven to be powerful, if you can find some way
to harness it:
crowd-sourcing
can perform tasks and solve collaborative
problems, crowd-funding
can raise substantial financing.

I suspect crowd-data will similarly become an effective way to create
large, realistic databases.

A great application of this is the medical world, where many
people post to health forums raising medical problems, possible side
effects from drugs and vaccines, etc. Why not collect all such posts
to find previously undiscovered problems? In
fact, this
paper describes just that: the authors extracted the nasty side
effects of statin
drugs based on posts to online health forums.
Similarly, this
abstract describes a system that used crowd-data to spot nasty
side effects
from Singulair,
years before
the FDA
issued a warning.
The VAERS
database, which gathers parent-reported problems after children
receive vaccines, is another example.

Unfortunately the drug safety trials that take place before a drug can be
released
are not
especially trustworthy. Here's a scary quote from that interview:

When you look at the highest quality medical studies, the odds that a study will favor the use of a new drug are 5.3 times higher for commercially funded studies than for noncommercially funded studies.

And that was 7 years ago! I imagine the situation has only gotten worse.

When a new drug is released, the true, unbiased
drug trial begins when millions of guinea-pigs start taking
taking it. Crowd-data makes it possible to draw conclusions from that
that post-market drug trial.

Of course there are challenging tradeoffs: crowd-data, being derived
from "ordinary people" without any rigorous standard collection
process, can be dirty, incomplete and reflect sampling bias (only people
experiencing nasty side effects speak up). For these reasons,
old-fashioned journals turn their noses up at papers drawing
conclusions from crowd-data.

Nevertheless, I believe such limitations are more than offset
by the real-time nature and shear scale the millions of people,
constantly posting information over time. Inevitably, trustworthy
patterns will emerge over the noise. Unlike the synthetic drug trial,
this data is as real as you can get: sure, perhaps the drug seemed
fine in the carefully controlled pre-market testing, but then out in
the real world, unexpected interactions can suddenly emerge.
Crowd-data will enable us to find such cases quickly and reliably, as
long as we still have enough willing guinea-pigs!

Fast forward a few years and I expect crowd-data will be an excellent
means of drawing conclusions, and will prove more reliable than the
company-funded pre-market drug trials.

2 comments:

Wow, I was searching for Lucene help for this y libraris a bit new for me now for my aging brains, and found this post - a bit unexpected for me. Mike, did you have unpleasant experience with statins (I don't know you age, but if you did i would be another valuable piece of authentic experience). And thank you very much for Lucene guides - helped me out many times I stumbled.

That's why many people think that drugs like statins are really good and effective because of the advertisement they did for it. What we didn't know is the side effects it can give a user until they used it.

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About Me

Michael loves building software; he's been building search engines for more than a decade. In 1999 he co-founded iPhrase Technologies, a startup providing a user-centric enterprise search application, written primarily in Python and C. After IBM acquired iPhrase in 2005, Michael fell in love with Lucene, becoming a committer in 2006 and PMC member in 2008. Michael has remained an active committer, helping to push Lucene to new places in recent years. He's co-author of Lucene in Action, 2nd edition. In his spare time Michael enjoys building his own computers, writing software to control his house (mostly in Python), encoding videos and tinkering with all sorts of other things.